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Computers better at diagnosing Alzheimer's disease from MR scans of the
brain

27 February 2008

Computers are able to diagnose Alzheimer's disease faster and more
accurately than experts, according to research published in the journal
Brain. The findings may help ensure that patients are diagnosed
earlier, increasing treatment options.

A team of researchers led by scientists at the Wellcome Trust Centre for
Neuroimaging at University College London, has shown that scans of patients
with Alzheimer's can be distinguished from those of healthy individuals and
patients with other forms of dementia. Computers can identify the
characteristic damage of Alzheimer's disease with an accuracy as high as
96%.

According to the Alzheimer's Research Trust, there are over 700,000
people currently living in the UK with dementia, of which Alzheimer's
disease, a neurodegenerative disease, is the most common form.

Alzheimer's is caused by the build up in the brain of plaques and
neurofibrillary tangles (tangles of brain tissue filaments), leading the
brain to atrophy. Definitive diagnosis is usually only possible after death,
but Alzheimer's is usually diagnosed using a combination of brain scans,
blood tests and interviews carried out by a trained clinician. The tests are
time consuming, and distinguishing the disease from other forms of dementia
can be difficult. The accuracy of diagnosis is only about 85%

"The advantage of using computers is that they prove cheaper, faster and
more accurate than the current method of diagnosis," explains Professor
Richard Frackowiak from the Wellcome Trust Centre for Neuroimaging. "The new
method makes an objective diagnosis without the need for human intervention.
This will be particularly attractive for areas of the world where there is a
shortage of trained clinicians and when a standardised reliable diagnosis is
needed, for example in drug trials."

The new method, developed by Professor Frackowiak’s team, works by
teaching a standard computer the differences between brain scans from
patients with proven Alzheimer’s disease and people with no signs of the
disease at all. The two conditions can be distinguished with a high degree
of accuracy on a single clinical MRI scan. This could be especially useful
for centres where facilities for extensive diagnostic workup are
unavailable. One use might be to reassure the worried elderly with mild
memory problems that they are not suffering from early Alzheimer’s.

The research tested scans from the US and the UK, from community and from
academic hospitals. The method was shown to be valid by testing it on scans
from people who had their status proven by pathological examination — the
gold standard. The results were uniformly encouraging.

The computer could be taught the distinction between normal and
Alzheimer’s with one set of scans and then used to correctly 'diagnose'
scans from another set. In all cases the results were better than the 86%
correct diagnostic rate of best clinical practice. The researchers also
found they could distinguish Alzheimer’s better than clinicians from a
similar disease called fronto-temporal dementia.

Professor Frackowiak emphasised that as symptoms from these diseases come
on after a considerable amount of damage has already occurred in the brain,
it is important to make an accurate diagnosis early to improve the chances
of effectively preventing deterioration.

"The next step is to see whether we can use the technique to reliably
track progression of the disease in a patient," says Professor Frackowiak.
"This could prove a powerful and non-invasive tool for screening the
efficacy of new drug treatments speedily, without a need for large costly
clinical trials."